The objective of this work is to design new compounds more active against SARS-CoV-2. This design study of new inhibitors on the main protease source of coronavirus (3CLpro) was conducted on ten molecules using Molecular Modeling techniques (Docking, QSAR, ADMET). Molecular docking between M5, M8 and M1 showing best, medium and low scores respectively. The active site residues revealed that the M5 ligand establishes more hydrogen bonds on all the ligands studied thus forming the most stable complex. Predicting the pIC50 of the molecules in the training set as a function of the variation in binding energy (∆∆G) to the pathogen, allowed us to develop a QSAR model accredited with very good statistical indicators R2 = 0.9137; S = 0.058; F = 52.942. The applicability domain of the model obtained from the lever method shows that all compounds belong to the applicability domain. Moreover, the reliability of this model allowed the design of twenty (20) new potential molecules with theoretical inhibitory concentration potentials (pIC50th) values superior to those of the molecules in the database. Finally, the pharmacokinetic profile of the proposed molecules was confirmed by the satisfaction of the Lipinski and ADMET.
| Published in | Modern Chemistry (Volume 10, Issue 2) |
| DOI | 10.11648/j.mc.20221002.12 |
| Page(s) | 30-47 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2024. Published by Science Publishing Group |
SARS-CoV-2, QSAR, Docking, ADMET
| [1] | W. J. Guan, Z. Y. Ni, Y. Hu, W. H. Liang, C. Q. Ou, J. X. He, L. Liu, H. Shan, C. L. Lei, D. Hui, B. Du, L. J. Li, G. Zeng, K. Y. Yuen, R. C. Chen, C. L. Tang, T. Wang, P. Y. Chen, J. Xiang, S. Y. Li, J. Wang et Z. Liang, «Clinical Characteristics of Coronavirus Disease 2019 in China,» The New England Journal of Medicine, vol. 382, n°%118, pp. 1708-1720, 2020. |
| [2] | D. Wang, B. Hu, C. Hu, F. Zhu, X. Liu, J. Zhang, B. Wang, H. Xiang, Z. Cheng, Y. Xiong, Y. Zhao, Y. Li, X. Wang et Z. Peng, «Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuhan,» JAMA, vol. 323, n°%111, p. 1061–1069, 2020. |
| [3] | Coronaviridae Study Group of the International Committee on Taxonomy of Viruses, «The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2,» Nature Microbiology, vol. 5, p. 536–544, 2020. |
| [4] | M. Julie, «CORONAVIRUS WORLDWIDE WEDNESDAY, JUNE 9, 2021: NEW CASES AND DEATHS IN 24 HOURS,» 08 Juin 2021. [Online]. Available: https://www.sortiraparis.com/actualites/a-paris/articles/212134-coronavirus-dans-le-monde-mardi-8-juin-2021-nouveaux-cas-et-morts-en-24h. [Access on 2021 July 09]. |
| [5] | R. Hilgenfeld, «From SARS to MERS: crystallographic studies on coronaviral proteases enable antiviral drug design.,» FEBS J, vol. 281, p. 4085–4096, 2014. |
| [6] | L. Zhang, D. Lin et X. Sun, «Crystal structure of SARS-CoV-2 main protease provides a basis for design of improved a-ketoamide inhibitors.,» Science, vol. 368, p. 409–412, 2020. |
| [7] | K. Anand, J. Ziebuhr et P. Wadhwani, « Coronavirus main proteinase (3CLpro) structure: basis for design of anti-SARS drugs.,» Science, vol. 300, p. 1763–1767, 2003. |
| [8] | D. Juckel, J. Dubuisson et S. Belouzard, «Coronaviruses, uncertain enemies.,» Med Sci, vol. 36, p. 633–641, 2020. |
| [9] | K. Anand, G. J. Palm, J. R. Mesters, S. G. Siddell, J. Ziebuhr et R. Hilgenfeld, «Structure of coronavirus main proteinase reveals combination of a chymotrypsin fold with an extra α-helical domain,» The EMBO Journal, vol. 21, n°%113, p. 3213–3224, 2002. |
| [10] | H. Yang, M. Yang, Y. Ding, Y. Liu, Z. Lou, Z. Zhou, L. Sun, L. Mo, S. Ye, H. Pang, G. Gao, K. Anand, M. Bartlam, R. Hilgenfeld et Z. Rao, «The crystal structures of severe acute respiratory syndrome virus main protease and its complex with an inhibitor,» Proceedings of the National Acamedy of Sciences of the United States of America, vol. 100, n°%123, p. 13190–13195, 2003. |
| [11] | A. Rathnayake, J. Zheng, Y. Kim, K. Perera, S. Mackin, D. Meyerholz, M. Kashipathy, K. Battaile, S. Lovell, S. Perlman, W. Groutas et K. Chang, «3C-like protease inhibitors block coronavirus replication in vitro and improve survival in MERS-CoV-infected mice,» Sci. Transl. Med, vol. 12, n°%1557, pp. 1-16, August 2020. |
| [12] | M. J. Frisch, G. W. Trucks, H. B. Schlegel et G. E. Scuseria, «Gaussian 09, Revision A.02,» Gaussian, Inc., Wallingford CT, 2009. |
| [13] | S. Chaltterjee, A. Hadi et B. Price, «Regression Analysis by Examples,» Wiley VCH: New York, 2000. |
| [14] | H. Phuong, «Synthesis and quantitative structure/activity relationship study (QSAR/2D) of Benzo[c]phenanthridine analogues,» France, 2007. |
| [15] | M. Excel, 2016. |
| [16] | E. Pettersen, T. Goddard, C. Huang, G. Couch, D. Greenblatt, E. Meng et T. Ferrin, «UCSF Chimera--a visualization system for exploratory research and analysis,» J. Comput. Chem., vol. 25, n°%113, pp. 1605-1612, 2004. |
| [17] | J. Fantini et N. Yahi, «Structural and molecular modelling studies reveal a new mechanism of action of Chloroquine and hydroxychloroquine against SARS-CoV-2 infection,» International Journal of Antimicrobial Agents, vol. 55, n°%15, p. 105960, May 2020. |
| [18] | A. Elfiky, «Ribavirin, Remdesivir, Sofosbuvir, and Tenofovir against SARS-CoV-2 RNA dependent RNA polymerase (RdRp): A molecular docking study,» Life Sci., vol. 253, p. 117592, 2020. |
| [19] | A. Kumar, A. Kumar, G. Tiwari, R. Kumar et N. Misra, «In Silico Investigations on the Potential Inhibitors for COVID-19 Protease,» arXiv: 2003.10642, 2020. |
| [20] | T. A. K. a. J. M. M. Roy Dennington, «GaussView, Version 6,» Semichem Inc. Shawnee Mission KS, 2016. |
| [21] | C. Lipinski, F. Lombardo, B. Dominy et P. Feeney, «Experimental and computational approaches to estimating solubility and permeability in drug discovery and development parameters,» Adv. Drug Deliv. Rév., vol. 1–3, n°%146, p. 3–26, mars 2001. |
| [22] | C. Lipinski, «Lead and drug compounds: the rule of five revolution,» Drug Discovery Today: Technologies, vol. 1, n°%14, p. 337–341, décembre 2004. |
| [23] | A. Daina, O. Michielin et V. Zoete, «SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules.,» Sci Rep, vol. 7, p. 42717, 2017. |
| [24] | « The metabolism of a drug,» 2021. [Online]. Available: http://udsmed.u-strasbg.fr/pharmaco/pdf/DCEM1_Pharmacologie_chapitre_5_Metabolisme_des_medic.pdf.. [Accès le 20 fevrier 2021]. |
| [25] | S. Lee, G. Chang, I. Lee, J. Chung, K. Sung et K. No, «PreADMET,» 2021. [Online]. Available: https://preadmet.bmdrc.kr/. |
| [26] | F. W. Schueler, «Chemobiodynamics and drug design,» Acad. Med., vol. 36, n°%13, p. 285–286, 1961. |
| [27] | S.-Y. Yang, «Pharmacophore modeling and applications in drug discovery,» Drug Discov. Today, vol. 15, n°%111–12, p. 444–450, 2010. |
| [28] | J. Wang, P. Morin, W. Wang et A. P. A. Kollman, «Use of MM-PBSA in Reproducing the Binding Free Energies to HIV-1 RT of TIBO Derivatives and Predicting the Binding Mode to HIV-1 RT of Efavirenz by Docking and MM-PBSA.,» J. Am. Chem. Soc., vol. 123, pp. 5221-5230, 2001. |
| [29] | A. Fortuné, «Molecular Modeling Techniques applied to the Study and Optimization of Immunogenic Molecules and Modulators of Chemoresistance Drugs,» 2006. |
| [30] | L. Eriksson, J. Jaworska, A. Worth, M. D. Cronin, R. M. Mc Dowell et P. Gramatica, «Methods for Reliability and Uncertainty Assessment and for Applicability Evaluations of Classification- and Regression-Based QSARs,» Environmental Health Perspectives, vol. 111, n°%110, pp. 1361-1375, 2003. |
| [31] | L. Stryer, J. M. Berg et J. L. Tymoczo, Drug development, 7e éd., vol. 36, Médecine Sciences, 2013, p. 1029–1054. |
APA Style
Georges Stéphane Dembélé, Mamadou Guy-Richard Koné, Doh Soro, Fandia Konaté, Bibata Konaté, et al. (2022). Design of New Inhibitors to Fight Against the 3CLpro Protease of SARS-CoV-2 (COVID-19). Modern Chemistry, 10(2), 30-47. https://doi.org/10.11648/j.mc.20221002.12
ACS Style
Georges Stéphane Dembélé; Mamadou Guy-Richard Koné; Doh Soro; Fandia Konaté; Bibata Konaté, et al. Design of New Inhibitors to Fight Against the 3CLpro Protease of SARS-CoV-2 (COVID-19). Mod. Chem. 2022, 10(2), 30-47. doi: 10.11648/j.mc.20221002.12
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Download@article{10.11648/j.mc.20221002.12,
author = {Georges Stéphane Dembélé and Mamadou Guy-Richard Koné and Doh Soro and Fandia Konaté and Bibata Konaté and Nahossé Ziao},
title = {Design of New Inhibitors to Fight Against the 3CLpro Protease of SARS-CoV-2 (COVID-19)},
journal = {Modern Chemistry},
volume = {10},
number = {2},
pages = {30-47},
doi = {10.11648/j.mc.20221002.12},
url = {https://doi.org/10.11648/j.mc.20221002.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mc.20221002.12},
abstract = {The objective of this work is to design new compounds more active against SARS-CoV-2. This design study of new inhibitors on the main protease source of coronavirus (3CLpro) was conducted on ten molecules using Molecular Modeling techniques (Docking, QSAR, ADMET). Molecular docking between M5, M8 and M1 showing best, medium and low scores respectively. The active site residues revealed that the M5 ligand establishes more hydrogen bonds on all the ligands studied thus forming the most stable complex. Predicting the pIC50 of the molecules in the training set as a function of the variation in binding energy (∆∆G) to the pathogen, allowed us to develop a QSAR model accredited with very good statistical indicators R2 = 0.9137; S = 0.058; F = 52.942. The applicability domain of the model obtained from the lever method shows that all compounds belong to the applicability domain. Moreover, the reliability of this model allowed the design of twenty (20) new potential molecules with theoretical inhibitory concentration potentials (pIC50th) values superior to those of the molecules in the database. Finally, the pharmacokinetic profile of the proposed molecules was confirmed by the satisfaction of the Lipinski and ADMET.},
year = {2022}
}
TY - JOUR T1 - Design of New Inhibitors to Fight Against the 3CLpro Protease of SARS-CoV-2 (COVID-19) AU - Georges Stéphane Dembélé AU - Mamadou Guy-Richard Koné AU - Doh Soro AU - Fandia Konaté AU - Bibata Konaté AU - Nahossé Ziao Y1 - 2022/04/28 PY - 2022 N1 - https://doi.org/10.11648/j.mc.20221002.12 DO - 10.11648/j.mc.20221002.12 T2 - Modern Chemistry JF - Modern Chemistry JO - Modern Chemistry SP - 30 EP - 47 PB - Science Publishing Group SN - 2329-180X UR - https://doi.org/10.11648/j.mc.20221002.12 AB - The objective of this work is to design new compounds more active against SARS-CoV-2. This design study of new inhibitors on the main protease source of coronavirus (3CLpro) was conducted on ten molecules using Molecular Modeling techniques (Docking, QSAR, ADMET). Molecular docking between M5, M8 and M1 showing best, medium and low scores respectively. The active site residues revealed that the M5 ligand establishes more hydrogen bonds on all the ligands studied thus forming the most stable complex. Predicting the pIC50 of the molecules in the training set as a function of the variation in binding energy (∆∆G) to the pathogen, allowed us to develop a QSAR model accredited with very good statistical indicators R2 = 0.9137; S = 0.058; F = 52.942. The applicability domain of the model obtained from the lever method shows that all compounds belong to the applicability domain. Moreover, the reliability of this model allowed the design of twenty (20) new potential molecules with theoretical inhibitory concentration potentials (pIC50th) values superior to those of the molecules in the database. Finally, the pharmacokinetic profile of the proposed molecules was confirmed by the satisfaction of the Lipinski and ADMET. VL - 10 IS - 2 ER -
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